{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:6LNX5H4BFSCCKTPJ6JTJXRG5VB","short_pith_number":"pith:6LNX5H4B","canonical_record":{"source":{"id":"1908.05891","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-16T08:51:27Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"e26237956d39bbaaef2c18ea527d5d4f3547ac4c43945525590f4f5dd7c6104f","abstract_canon_sha256":"16de8d66f46877b376625458482765534b72a8946fa9995a75ca956113d8a4a6"},"schema_version":"1.0"},"canonical_sha256":"f2db7e9f812c84254de9f2669bc4dda865b0fcd09037a00e09c3124e093c5d2e","source":{"kind":"arxiv","id":"1908.05891","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.05891","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"arxiv_version","alias_value":"1908.05891v2","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.05891","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_12","alias_value":"6LNX5H4BFSCC","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_16","alias_value":"6LNX5H4BFSCCKTPJ","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_8","alias_value":"6LNX5H4B","created_at":"2026-07-05T00:01:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:6LNX5H4BFSCCKTPJ6JTJXRG5VB","target":"record","payload":{"canonical_record":{"source":{"id":"1908.05891","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-16T08:51:27Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"e26237956d39bbaaef2c18ea527d5d4f3547ac4c43945525590f4f5dd7c6104f","abstract_canon_sha256":"16de8d66f46877b376625458482765534b72a8946fa9995a75ca956113d8a4a6"},"schema_version":"1.0"},"canonical_sha256":"f2db7e9f812c84254de9f2669bc4dda865b0fcd09037a00e09c3124e093c5d2e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:01:03.456074Z","signature_b64":"x0RHQX1lLPOPhjtpXt5+irRZfGk2XdobT3kErcAYsjaKhHVVynJPAHixItKUruLtbA0dJcj/rujp+KTcIk8HCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2db7e9f812c84254de9f2669bc4dda865b0fcd09037a00e09c3124e093c5d2e","last_reissued_at":"2026-07-05T00:01:03.455657Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:01:03.455657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.05891","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:01:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"smSUT4py4uWqpsVY+j0Soo5hqKMDkAFqX2zfnhFsEyaxbO74QnZJNqtbk/RBhy+EmhZBuXhWl8MEAHkO2hclAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T14:50:32.956537Z"},"content_sha256":"697f73ea5e9a4b2673b4cd265c103abcabf41807fa955e5e09e4e1a7e7bbeaf5","schema_version":"1.0","event_id":"sha256:697f73ea5e9a4b2673b4cd265c103abcabf41807fa955e5e09e4e1a7e7bbeaf5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:6LNX5H4BFSCCKTPJ6JTJXRG5VB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Chenglei Wu, Lifeng Sun, Rui-Xiao Zhang, Tianchi Huang, Xin Yao","submitted_at":"2019-08-16T08:51:27Z","abstract_excerpt":"Federated learning (FL) enables on-device training over distributed networks consisting of a massive amount of modern smart devices, such as smartphones and IoT (Internet of Things) devices. However, the leading optimization algorithm in such settings, i.e., federated averaging (FedAvg), suffers from heavy communication costs and the inevitable performance drop, especially when the local data is distributed in a non-IID way. To alleviate this problem, we propose two potential solutions by introducing additional mechanisms to the on-device training.\n  The first (FedMMD) is adopting a two-stream"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.05891","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.05891/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:01:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OXLD71meD2ZRfEsU2FeCcvCRsap3X3sE4z1l7p+vGmfnqX9kOrIMioLWcvIpQv4DME4VBNs/Mhxn/mXDK+2rCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T14:50:32.957059Z"},"content_sha256":"4af9b6b916951ce635521b24acd77dd6d991cd6526f6e924f478fc8e0828ea41","schema_version":"1.0","event_id":"sha256:4af9b6b916951ce635521b24acd77dd6d991cd6526f6e924f478fc8e0828ea41"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/bundle.json","state_url":"https://pith.science/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-15T14:50:32Z","links":{"resolver":"https://pith.science/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB","bundle":"https://pith.science/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/bundle.json","state":"https://pith.science/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6LNX5H4BFSCCKTPJ6JTJXRG5VB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:6LNX5H4BFSCCKTPJ6JTJXRG5VB","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"16de8d66f46877b376625458482765534b72a8946fa9995a75ca956113d8a4a6","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-16T08:51:27Z","title_canon_sha256":"e26237956d39bbaaef2c18ea527d5d4f3547ac4c43945525590f4f5dd7c6104f"},"schema_version":"1.0","source":{"id":"1908.05891","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.05891","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"arxiv_version","alias_value":"1908.05891v2","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.05891","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_12","alias_value":"6LNX5H4BFSCC","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_16","alias_value":"6LNX5H4BFSCCKTPJ","created_at":"2026-07-05T00:01:03Z"},{"alias_kind":"pith_short_8","alias_value":"6LNX5H4B","created_at":"2026-07-05T00:01:03Z"}],"graph_snapshots":[{"event_id":"sha256:4af9b6b916951ce635521b24acd77dd6d991cd6526f6e924f478fc8e0828ea41","target":"graph","created_at":"2026-07-05T00:01:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1908.05891/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) enables on-device training over distributed networks consisting of a massive amount of modern smart devices, such as smartphones and IoT (Internet of Things) devices. However, the leading optimization algorithm in such settings, i.e., federated averaging (FedAvg), suffers from heavy communication costs and the inevitable performance drop, especially when the local data is distributed in a non-IID way. To alleviate this problem, we propose two potential solutions by introducing additional mechanisms to the on-device training.\n  The first (FedMMD) is adopting a two-stream","authors_text":"Chenglei Wu, Lifeng Sun, Rui-Xiao Zhang, Tianchi Huang, Xin Yao","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-16T08:51:27Z","title":"Federated Learning with Additional Mechanisms on Clients to Reduce Communication Costs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.05891","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:697f73ea5e9a4b2673b4cd265c103abcabf41807fa955e5e09e4e1a7e7bbeaf5","target":"record","created_at":"2026-07-05T00:01:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"16de8d66f46877b376625458482765534b72a8946fa9995a75ca956113d8a4a6","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-16T08:51:27Z","title_canon_sha256":"e26237956d39bbaaef2c18ea527d5d4f3547ac4c43945525590f4f5dd7c6104f"},"schema_version":"1.0","source":{"id":"1908.05891","kind":"arxiv","version":2}},"canonical_sha256":"f2db7e9f812c84254de9f2669bc4dda865b0fcd09037a00e09c3124e093c5d2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f2db7e9f812c84254de9f2669bc4dda865b0fcd09037a00e09c3124e093c5d2e","first_computed_at":"2026-07-05T00:01:03.455657Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:01:03.455657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x0RHQX1lLPOPhjtpXt5+irRZfGk2XdobT3kErcAYsjaKhHVVynJPAHixItKUruLtbA0dJcj/rujp+KTcIk8HCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:01:03.456074Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.05891","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:697f73ea5e9a4b2673b4cd265c103abcabf41807fa955e5e09e4e1a7e7bbeaf5","sha256:4af9b6b916951ce635521b24acd77dd6d991cd6526f6e924f478fc8e0828ea41"],"state_sha256":"21b58eaee0ed5382cead772ca1ea9bf35939e032d0da744b0b13de7bd7d85a30"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NT6Lw95B/v3PeQ8p359xgN/CEp2vHzbYHBJIKiwdX1dFZI/LSew8LsgUjQ9NCM0ETAIGdbhR3kYDxn7RDIjiBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T14:50:32.961240Z","bundle_sha256":"d1b2e00a1e993f6500a229bff4ee9fb93b8a22e6e6ad264c0175c863517f44e3"}}